•This article reviews the state-of-the-art of existing DSC literature in detail from both academic and industrial points of view.•It identifies key limitations and prospects in DSC, summarizes prior ...research and identifies knowledge gaps.•It provides a development framework as a roadmap for future research and practice.
Suppliers, partners, companies and dealers in supply chains do use, generate and share information with others. These associations lead to a multitude of challenges and opportunities within the supply chains. A Digital Supply Chain (DSC) is a smart, value-driven, efficient process to generate new forms of revenue and business value for organizations and to leverage new approaches with novel technological and analytical methods DSC is not about whether goods and services are digital or physical, it is about the way how supply chain processes are managed with a wide variety of innovative technologies, e.g. unmanned aerial vehicles, cloud computing, and internet of things, among others. Recent literature highlights the importance of DSC and many industrial researchers discuss its applications. This article reviews the state-of-the-art of existing DSC literature in detail from both academic and industrial points of view. It identifies key limitations and prospects in DSC, summarizes prior research and identifies knowledge gaps by providing advantages, weaknesses and limitations of individual methods The article also aims at providing a development framework as a roadmap for future research and practice.
This paper reviews the best-known differential scanning calorimetries (DSCs), such as conventional DSC, microelectromechanical systems-DSC, infrared-heated DSC, modulated-temperature DSC, gas ...flow-modulated DSC, parallel-nano DSC, pressure perturbation calorimetry, self-reference DSC, and high-performance DSC. Also, we describe here the most extensive applications of DSC in biology and nanoscience.
•Fast DSC with liquids in the temperature range −100°C to +225°C, at scan rates up to 1000°C/s.•Reproducibility of calculated enthalpy values ca ±7%, of peak temperature values ca ±1°C.•Resolution ...for measuring lysozyme denaturation between 0.1% and 1% lysozyme solution in water by weight.•Measurements for bovine serum show good agreement with DSC results, but typically 1000× faster.•Results for olive oil give good agreement for the freezing peak, a temperature shift for the melting peak compared to DSC.
Based on a modified version of standard chips for fast differential scanning calorimetry, DSC of liquid samples has been performed at temperature scan rates of up to 1000°C/s. This paper describes experimental results with the protein lysozyme, bovine serum, and olive oil. The heating and cooling rate of the sensor is measured for temperature scan rates of up to 1300°C/s with water and 2-butanol, in the temperature range of −90°C/s to +130°C/s. The lysozyme is measured at temperature scan rates varying from 10°C/s to 400°C/s and in concentrations between 0.1% and 10% protein by weight. The bovine serum measurements show two main peaks, in good agreement with standard DSC measurements. Olive oil has been measured, with good agreement for the cooling curve and qualitative agreement for the heater curve, compared to DSC measurements.
Multi-echo, multi-contrast methods are increasingly used in dynamic imaging studies to simultaneously quantify R2∗ and R2. To overcome the computational challenges associated with nonlinear least ...squares (NLSQ) fitting, we propose a generalized linear least squares (LLSQ) solution to rapidly fit R2∗ and R2.
Spin- and gradient-echo (SAGE) data were simulated across T2∗ and T2 values at high (200) and low (20) SNR. Full (four-parameter) and reduced (three-parameter) parameter fits were implemented and compared with both LLSQ and NLSQ fitting. Fit data were compared to ground truth using concordance correlation coefficient (CCC) and coefficient of variation (CV). In vivo SAGE perfusion data were acquired in 20 subjects with relapsing-remitting multiple sclerosis. LLSQ R2∗ and R2, as well as cerebral blood volume (CBV), were compared with the standard NLSQ approach.
Across all fitting methods, T2∗ was well-fit at high (CCC = 1, CV = 0) and low (CCC ≥ 0.87, CV ≤ 0.08) SNR. Except for short T2∗ values (5–15 ms), T2 was well-fit at high (CCC = 1, CV = 0) and low (CCC ≥ 0.99, CV ≤ 0.03) SNR. In vivo, LLSQ R2∗ and R2 estimates were similar to NLSQ, and there were no differences in R2∗ across fitting methods at high SNR. However, there were some differences at low SNR and for R2 at high and low SNR. In vivo NLSQ and LLSQ three parameter fits performed similarly, as did NLSQ and LLSQ four-parameter fits. LLSQ CBV nearly matched the standard NLSQ method for R2∗- (0.97 ratio) and R2-CBV (0.98 ratio). Voxel-wise whole-brain fitting was faster for LLSQ (3–4 min) than NLSQ (16–18 h).
LLSQ reliably fit for R2∗ and R2 in simulated and in vivo data. Use of LLSQ methods reduced the computational demand, enabling rapid estimation of R2∗ and R2.
This study explores the application of an Internet of Things (IoT)-driven reflectance-based multimode colorimeter for real-time monitoring of the crystallization process in oleogels-a novel class of ...structured lipids gaining popularity in the food industries. These structured lipids offer a healthier alternative to solid fats, but their texture and stability rely on precise control of crystallization process. Traditional monitoring methods, such as atomic force microscopy and spectroscopy, are expensive and lack real-time capabilities. The proposed device can operate in two modes: quality testing and process monitoring modes. In the quality testing mode, the device exhibits superior color accuracy compared to a commercial device, making it a reliable tool for color assessment (ΔE values < 10). In the process monitoring mode, the device effectively tracks crystallization kinetics at different incubation temperatures (5 °C, 15 °C, and 25 °C), revealing the impact of sunflower lecithin on primary and secondary crystallization phases. Further, the temperature vs. L* data offers more profound insights into oleogel crystallization, validated by Differential Scanning Calorimetry (DSC) analysis. Additionally, the device's performance was tested by monitoring the crystallization process of butter. The results obtained from the device closely matched the DSC findings, which enhanced our understanding of the crystallization processes in butter. This showcases the potential of the device for analyzing food samples.
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•Development of an innovative IoT-driven reflectance colorimeter working in quality testing and process monitoring modes.•Quality Testing mode demonstrated better color accuracy compared to a commercial device.•In Process Monitoring mode, the device effectively tracked the crystallization kinetics of oleogels.•Strong positive correlations between the proposed device and DSC results validate its efficiency.•The testing of the developed device using butter sample is matched with the result obtained from DSC analysis.
The Rock-Eval pyrolysis-stage derived parameters such as free hydrocarbons (S1), heavier pyrolysis-hydrocarbons (S2), pyrolyzable carbon (PC) and pyrolysis Tmax (from S2 curve) have received ...considerable interest for source-rock screening and thermal maturity assessment. On the other hand, the Rock-Eval oxidation-stage S4CO2 curve, which gives the amount of residual carbon (RC), only recently has received some interest. While the pyrolysis-stage S2 temperature-peak (Tmax) is conventionally used as a maturity proxy, in this work we show that the temperature-peak of S4CO2 curve (S4Tmax) can also be used as a thermal maturity proxy for shales. For overmature and low-TOC shale samples, showing asymmetric S2 shape and concomitantly producing doubtful Tmax, the S4 curves showed symmetric nature and consequently the S4Tmax was observed to be a reliable thermal maturity estimate. While the S4Tmax clearly resolved immature and overmature shales, for the early mature and peak mature shales the S4Tmax showed overlapping values. S4Tmax of pre-pyrolyzed and pyrolyzed masses showed good positive correlation with differential scanning calorimetry temperature-peak (DSCTpeak), and consequently indicated its applicability as a thermal maturity proxy. When early mature pre-pyrolyzed samples were directly analyzed using the Rock-Eval oxidation stage, the S4 curves showed formation of two sub-peaks, and consequently the Tmax was observed to decrease. It is recommended that analysts and interpreters should thoroughly cross-check S2 curves before reporting data, and in case of asymmetric or unreliable S2 curves, the S4Tmax can be used as a maturity proxy.
•Importance of Rock-Eval oxidation stage.•S4Tpeak as a thermal maturity proxy for shales.•Critical monitoring of Rock-Eval S2 curves.
•XRD, FT-IR, UV–Vis and Raman spectroscopy.•Photoluminescence.•DFT calculations.
A new intercalation crystalline polymer compound of bis m-nitroanilinium tetrachlorocadmate (II) {(m-C6H7N2O2)2CdCl4}n ...was synthesized and analyzed using single crystal SXRD, differential scanning calorimetry (DSC), DFT analysis, thermal gravimetric analysis (TGA) and FT-IR, Raman, UV–Vis, fluorescence spectroscopy techniques. X-ray diffraction analyses (SXRD, PXRD) show a layered structure consisting of alternating organic bilayers and two-dimensional inorganic sheets in which each CdCl6 octahedron shares four corners with adjacent octahedra. The crystal packing is consolidated by means of classic and non-classic hydrogen bonds and π-π interactions. At room temperature photoluminescence spectra of {(m-C6H7N2O2)2CdCl4}n yield broad peaks in the 469–770 nm range with full width at half maximum (FWHM) values up to 153 nm. Besides, this compound exhibits a semiconducting behavior with bright red-light under 360 nm ultraviolet photoexcitation and possesses a large Stokes shift and direct band gap of 2.69 eV which overlaps well with solar spectrum. The CIE chromaticity coordinates of {(m-C6H7N2O2)2CdCl4}n are (x = 0.4704 and y = 0.4523). The color rendering index CRI and the low correlated color temperature CCT are 84 and 2861 K, respectively. Electronic structure (BS, DOS and PDOS), and optical properties (dielectric constant ε(ω), refractive index n(ω), reflectivity R(ω), absorption coefficient α(ω), optical conductivity σ(ω) and energy loss function L(ω) with the incident photon energy) were determined using (DFT) calculations by CASTEP code.
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Reliable interpretation of the changes occurring in the samples during their heating is ensured by using more than one measurement technique. This is related to the necessity of eliminating the ...uncertainty resulting from the interpretation of data obtained by two or more single techniques based on the study of several samples analyzed at different times. Accordingly, the purpose of this paper is to briefly characterize thermal analysis techniques coupled to non-thermal techniques, most often spectroscopic or chromatographic. The design of coupled thermogravimetry (TG) with Fourier transform infrared spectroscopy (FTIR), TG with mass spectrometry (MS) and TG with gas chromatography/mass spectrometry (GC/MS) systems and the principles of measurement are discussed. Using medicinal substances as examples, the key importance of coupled techniques in pharmaceutical technology is pointed out. They make it possible not only to know precisely the behavior of medicinal substances during heating and to identify volatile degradation products, but also to determine the mechanism of thermal decomposition. The data obtained make it possible to predict the behavior of medicinal substances during the manufacture of pharmaceutical preparations and determine their shelf life and storage conditions. Additionally, characterized are design solutions that support the interpretation of differential scanning calorimetry (DSC) curves based on observation of the samples during heating or based on simultaneous registration of FTIR spectra and X-ray diffractograms (XRD). This is important because DSC is an inherently non-specific technique. For this reason, individual phase transitions cannot be distinguished from each other based on DSC curves, and supporting techniques are required to interpret them correctly.
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